Kooperativer Bibliotheksverbund

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Format: VIII, 191 p. 78 illus., 68 illus. in color. , online resource.

Edition: 1st ed. 2022.

ISBN: 9783030961886

Series Statement: Springer Proceedings in Complexity,

Content: This book contains a selection of the latest research in the field of Computational Social Science (CSS) methods, uses, and results, as presented at the 2021 annual conference of the Computational Social Science Society of the Americas (CSSSA). Computational social science (CSS) is the science that investigates social and behavioral dynamics through social simulation, social network analysis, and social media analysis. The CSSSA is a professional society that aims to advance the field of computational social science in all areas, including basic and applied orientations, by holding conferences and workshops, promoting standards of scientific excellence in research and teaching, and publishing research findings and results.

Note: Chapter 1 - Effects of Assortativity on Consensus Formation with Heterogeneous Agents (Ece Mutlu and Ozlem Ozmen Garibay) -- Chapter 2 - Quantifying Polish Anti-Semitism in Twitter: A Robust Unsupervised Approach with Signal Processing (Peter Chew) -- Chapter 3 - On Modeling Evolution in Continuous Spaces (Robin Clark and Steven Kimbrough) -- Chapter 4 - Economic Sanctions and Consumer Behavior in Target States: An Agent-Based Model of Boycott Movements (Rena Sung and Jonghyuk Park) -- Chapter 5 - Scheduler dependencies in Agent-Based Models: A case-study using a contagion model (Srikanth Mudigonda; Santiago Nunez-Corrales; Rajesh Venkatachalapathy and Jeffrey Graham) -- Chapter 6 - Exploring the Impact of Social Network Density and Agent Openness on Societal Polarization (Justin Mittereder; Robert Carroll; Brandon Frulla and Stephen Davies) -- Chapter 7 - Learning Actor Preferences by Evolution (H Van Dyke Parunak) -- Chapter 8 - Drivers and Predictors of COVID-19 Vaccine Hesitancy in Virginia (Asal Pilehvari; Jason Ton; Mukundan Ram Mohan; Achla Marathe and Anil Vullikanti) -- Chapter 9 - The Spreading-Activation Framework Does Not Explain the Effects of Degree and Clustering on Spoken Word Recognition (Leo Niehorster-Cook) -- Chapter 10 - Engineering Decentralized Enterprises: Emergent Mission Accomplishment without Centralized Command and Control (Michael Norman; Paul Silvey; Matthew Koehler and Kirbi Joe) -- Chapter 11 - An Agent-Based Approach to Classical Competitive Prices (Jonathan Cogliano, Roberto Veneziani and Naoki Yoshihara) -- Chapter 12 - Machine Learning Reveals Adaptive COVID-19 Narratives in Online Anti-Vaccination Network (Richard Sear; Rhys Leahy; Nicholas Johnson Restrepo; Yonatan Lupu and Neil Johnson) -- Chapter 13 - Agentization of Two Population-Driven Models of Mathematical Biology(John Stevenson).

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783030961879

Additional Edition: Printed edition: ISBN 9783030961893

Additional Edition: Printed edition: ISBN 9783030961909

Language: English

DOI: 10.1007/978-3-030-96188-6

URL: https://doi.org/10.1007/978-3-030-96188-6

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UID:

Format: XIII, 399 p. 167 illus., 151 illus. in color. , online resource.

Edition: 1st ed. 2021.

ISBN: 9783030775179

Series Statement: Springer Proceedings in Complexity,

Content: This book presents the latest research into CSS methods, uses, and results, as presented at the 2019 annual conference of the CSSSA. This conference was held in Santa Fe, New Mexico, October 24 - 27, 2019, at the Drury Plaza Hotel. What follows is a diverse representation of new results and approaches for using the tools of CSS and agent-based modeling (ABM) for exploring complex phenomena across many different domains. Readers will therefore not only have the results of these specific projects on which to build, but will also gain a greater appreciation for the broad scope of CSS, and have a wealth of case-study examples that can serve as meaningful exemplars for new research projects and activities. The Computational Social Science Society of the Americas (CSSSA) is a professional society that aims to advance the field of CSS in all its areas, from fundamental principles to real-world applications, by holding conferences and workshops, promoting standards of scientific excellence in research and teaching, and publishing novel research findings.

Note: Chapter 1 - Encoding Protest Duration in an Agent-Based Model as Characteristic PhaseTransitions (Brian Goode and Bianica Pires ) -- Chapter 2 - System-wide Policy Solutions for Water Scarcity Issues (Saeed Langarudi, Ashley Page, Connie Maxwell, Yining Bai, Babak Bahaddin, and Alexander Fernald) -- Chapter 3 - More or Faster? Technology Subsidy Policy, Additional Adoptions, and Accelerated Diffusion (D. Cale Reeves, and Varun Rai) -- Chapter 4 - Assessing the Potential of Crowd-shipping for Food Rescue Logistics Using Agent-based Modeling (Anuj Mittal, Nilufer Oran Gibson, and Caroline Krejci) -- Chapter 5 - The Cat and Mouse Dynamics of Getting Around the Law (Daria Roithmayr, Fei Fang, and Justin Chin) -- Chapter 6 - Social Primitives: Exploring Spark of Life Collective Behavior in Agent Based Models (Srikanth Mudigonda, and Milton Friesen) -- Chapter 7 - Wealth dynamics in the presence of network structure and primitive cooperation ( Rajesh Venkatachalapathy, Stephen Davies, and William Nehrboss) -- Chapter 8 - Resistance of Communities Against Conspiracies ( Amirarsalan Rajabi, Seyyedmilad Talebzadehhosseini, and Ivan Garibay) -- Chapter 9 - Capturing the Production of Innovative Ideas: An Online Social Network Experiment and "Idea Geography" Visualization ( Yiding Cao, Yingjun Dong, Minjun Kim, Neil Maclaren, Ankita Kulkarni, Shelley Dionne, Francis Yammarino, and Hiroki Sayama) -- Chapter 10 - An Agent-Based Model to Understand Simple Theory of Mind: Belief Representation Systematic Approach (BRSA) ( Zahrieh Yousefi, Dietmar Heinke, Ian Apperly, and Peer-Olaf Siebers) -- Chapter 11 - A Model of Emergence featuring Social Mechanisms of Information Compression (Loren Demerath, James Reid, and E. Dante Suarez) -- Chapter 12 - Social viscosity, fluidity and turbulence in collective perceptions of color: an agent-based model of color scale convergence (Juan Salamanca, and Santiago Núñez-Corrales).-Chapter 13 - Abandoned Battlegrounds An Agent-Based Model of Campaign Behavior Change with Proportional Allocation of Electors (John Silver: Electoral College) -- Chapter 14 - Global News Sentiment Analysis (Eric Castellanos, Hang Xie, and Paul Brenner) -- Chapter 15 - Corruption and the effects of influence within social networks: An agent-based model of the Lava Jato scandal (Amira Al-Khulaidy, and Valentin Vergara Hidd) -- Chapter 16 - The Degree-Dependent Threshold Model: Towards a Better Understanding of Opinion Dynamics on Online Social Networks ( *Ece Mutlu, and Ivan Garibay) -- Chapter 17 - Inside the Mind of the Nonfiler: An Agent-Based Modeling Approach (Melissa Vigil, Thi Nguyen, and Ellen Badgley) -- Chapter 18 - A Complex-Systems Agenda for Influencing Policy Analysis ( Paul Davis, Tim McDonald, Ann Pendleton-Jullian, Angela O'Mahony, and Osonde Osoba) -- Chapter 19 - The Evolution of Sharing in the Dictator Game (Jeffrey Schank) -- Chapter 20 - Capturing the Effects of Gentrification on Property Values: An Agent-Based Modeling Approach (Niloofar Bagheri-Jebelli, Andrew T. Crooks, and William G. Kennedy) -- Chapter 21 - Exogenous Shocks Lead to Increased Responsiveness and Shifts in Sentimental Resilience in Online Discussions (Chathika Gunaratne, Subash Ray, Caroline Alves, and Maria Waldl) -- Chapter 22 - Decision-Adjusted Modeling for Imbalanced Classification: Predicting Rooftop Solar Panel Adoption in Rural Virginia (Zhihao Hu, Xinwei Deng, Achla Marathe, Samarth Swarup and Anil Vullikanti) -- Chapter 23 - An agent-based model of social fabric seen as an emergent behavior in cities (Gamaliel Palomo, Mario Siller, Arnaud Grignard, and Luis Alonso) -- Chapter 24 - Modifying human facial impression ( Amanda Song, Chad Atalla, Bartholomew Tam, Linjie Li, and Garrison Cottrell) -- Chapter 25 - Modeling Genocide: An Agent-Based Model of Bystander Motivation and Societal Restraints (Elizabeth von Briesen, Amy Canevello, Samira Shaikh, John Cox, and Mirsad Hadžikadić) -- Chapter 26 - Deep Agent: A Framework for Information Spread and Evolution in Social Networks ( Ivan Garibay, Toktam Oghaz, and Niloofar Yousefi) -- Chapter 27 - Negative Influence Gradients Lead to Lowered Information Processing Capacity on Social Networks ( Nisha Baral, Chathika Gunaratne, Chathura Jayalath, William Rand, Chathurani Senevirathna, and Ivan Garibay) -- Chapter 28 - Complex Systems Analysis of Transplant Center Performance Metrics (David Dixon).

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783030775162

Additional Edition: Printed edition: ISBN 9783030775186

Additional Edition: Printed edition: ISBN 9783030775193

Language: English

Subjects: Sociology

Keywords: Aufsatzsammlung ; Konferenzschrift

DOI: 10.1007/978-3-030-77517-9

URL: https://doi.org/10.1007/978-3-030-77517-9

URL: Volltext  (URL des Erstveröffentlichers)

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UID:

Format: IX, 279 p. 131 illus., 123 illus. in color. , online resource.

Edition: 1st ed. 2021.

ISBN: 9783030834180

Series Statement: Springer Proceedings in Complexity,

Content: This book is comprised of the latest research into CSS methods, uses, and results, as presented at the 2020 annual conference of the Computational Social Science Society of the Americas (CSSSA). Computational social science (CSS) is the science that investigates social and behavioral dynamics through social simulation, social network analysis, and social media analysis. The CSSSA is a professional society that aims to advance the field of computational social science in all areas, including basic and applied orientations, by holding conferences and workshops, promoting standards of scientific excellence in research and teaching, and publishing research findings and results. The above-mentioned conference was held virtually, October 8 - 11, 2020. What follows is a diverse representation of new results and approaches to using the tools of CSS and agent-based modeling (ABM) in exploring complex phenomena across many different domains. Readers will therefore not only have the results of these specific projects upon which to build, along with a wealth of case-study examples that can serve as meaningful exemplars for new research projects and activities, they will also gain a greater appreciation for the broad scope of CSS.

Note: Chapter 1 - Creating Intelligent Agents: Combining Agent-Based Modeling with Machine Learning (Dale Brearcliffe and Andrew Crooks) -- Chapter 2 - Envy splits societies into a lower and a upper class (Claudius Gros) -- Chapter 3 - Effects of Non-Cognitive Factors on Post-Secondary Persistence of Deaf Students: An Agent-Based Modeling Approach (Marie Alaghband and Ivan Garibay) -- Chapter 4 - Comparing Agent-Based Modeling to Cooperative Game Theory and Human Behavior (Andrew Collins) -- Chapter 5 - Analyzing transnational narratives in Twitter: an unsupervised approach using PARAFAC (Peter Chew and Jonathan Chew) -- Chapter 6 - In-Silico models with greater fidelity to social processes: towards ABM platforms with realistic concurrency (Santiago Núñez-Corrales, Milton Friesen, Srikanth Mudigonda, Rajesh Venkatachalapathy and Jeffrey Graham) -- Chapter 7 - Dynamics of Information Perception in Management of Commons (Saeed Langarudi, Carlos Silva and Sam Fernald) -- Chapter 8 - Psychology from Stigmergy (H. Van Dyke Parunak) -- Chapter 9 - CD-SEIZ: Cognition-Driven SEIZ Compartmental Model for the Prediction of Information Cascades on Twitter (Ece Mutlu, Ivan Garibay and Amirarsalan Rajabi) -- Chapter 10 - Cultural Drift, Indirect Minority Influence, Network Structure and Their Impacts on Cultural Change and Diversity (Jiin Jung, Aaron Bramson, William Crano, Scott Page and John Miller) -- Chapter 11 - An agent-based model to evaluate the perception of safety in informal settlements (Leticia Izquiero, Gamaliel Palomo, Arnaud Grignard, Luis Alonso, Mario Siller and Kent Larson) -- Chapter 12 - Study of Altruism as a Behavioral Trait in Game Theory Network Dynamics with Prisoner Dilemma Games (William Leibzon) -- Chapter 13 - Analyzing the potential impact of nonpharmaceutical interventions on the spread of COVID-19 (COVID-19 work in progress) (Matthew Koehler, David Slater, Garry Jacyna and James Thompson).-Chapter 14 - An Agent-Based Model of Infectious Diseases that Incorporates the Role of Immune Cells and Antibodies (Shigeaki Ogibayashi) -- Chapter 15 - Heterogeneity in populations and behaviors: An agent-based model of the social spread of COVID-19 (Nicholas Willems, Cale Reeves, Vivek Shastry and Varun Rai) -- Chapter 16 - Work In Progress: COVID-19 Policy Evaluation (CoPE) Tool: An agent-based model for ex-ante evaluation of policy designs and behavioral responses to COVID-19 (Vivek Shastry, Cale Reeves, Nicholas Willems and Varun Rai) -- Chapter 17 - Investigating dynamics of COVID-19 spread and containment with agent-based modelling (Amirarsalan Rajabi, Alexander Mantzaris, Ece Mutlu and Ivan Garibay) -- Chapter 18 - Purchasing Power to the People: An Agent-Based Simulation of Pandemic Economic Recovery (Youngsun Hwang, Joseph Immormino and Glenn-Iain Steinback) -- Chapter 19 - Agent-based models of Quadratic Voting (Jacob Kelter, Andreas Bugler and Uri Wilensky) -- Chapter 20 - Towards a model of the national market system: fragmented and heterogenous venues (Brian Tivnan, Carl Burke, Matthew Koehler, Matthew Mcmahon And Jason Veneman) -- Chapter 21 - Online Rejection Influence on Behavior Deviancy and Radicalization: An Agent-Based Model Approach (Hanin Alhaddad, Nisha Baral and Ivan Garibay) -- Chapter 22 - An agent-based model of digitally-mediated farmer transportation collaboration (Narjes Sadeghiamirshahidi, Anuj Mittal and Caroline Krejci) -- Chapter 23 - Geometries of Desire: Simulating Rene Girard's Mimetic Theory (Graham Sack) -- Chapter 24 - Can Institutionalization Prevent the Depletion of Groundwater Resources? (Mehdi Moghadam Manesh, Saeed Langarudi and Birgit Kopainsky).

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783030834173

Additional Edition: Printed edition: ISBN 9783030834197

Additional Edition: Printed edition: ISBN 9783030834203

Language: English

DOI: 10.1007/978-3-030-83418-0

URL: https://doi.org/10.1007/978-3-030-83418-0

URL: Volltext  (URL des Erstveröffentlichers)

URL: lizenzpflichtig

UID:

Format: 1 online resource (199 pages)

Edition: 1st ed. 2022.

ISBN: 3-030-96188-5

Series Statement: Springer Proceedings in Complexity,

Content: This book contains a selection of the latest research in the field of Computational Social Science (CSS) methods, uses, and results, as presented at the 2021 annual conference of the Computational Social Science Society of the Americas (CSSSA). Computational social science (CSS) is the science that investigates social and behavioral dynamics through social simulation, social network analysis, and social media analysis. The CSSSA is a professional society that aims to advance the field of computational social science in all areas, including basic and applied orientations, by holding conferences and workshops, promoting standards of scientific excellence in research and teaching, and publishing research findings and results.

Note: Chapter 1 - Effects of Assortativity on Consensus Formation with Heterogeneous Agents (Ece Mutlu and Ozlem Ozmen Garibay) -- Chapter 2 - Quantifying Polish Anti-Semitism in Twitter: A Robust Unsupervised Approach with Signal Processing (Peter Chew) -- Chapter 3 - On Modeling Evolution in Continuous Spaces (Robin Clark and Steven Kimbrough) -- Chapter 4 - Economic Sanctions and Consumer Behavior in Target States: An Agent-Based Model of Boycott Movements (Rena Sung and Jonghyuk Park) -- Chapter 5 - Scheduler dependencies in Agent-Based Models: A case-study using a contagion model (Srikanth Mudigonda; Santiago Nunez-Corrales; Rajesh Venkatachalapathy and Jeffrey Graham) -- Chapter 6 - Exploring the Impact of Social Network Density and Agent Openness on Societal Polarization (Justin Mittereder; Robert Carroll; Brandon Frulla and Stephen Davies) -- Chapter 7 - Learning Actor Preferences by Evolution (H Van Dyke Parunak) -- Chapter 8 - Drivers and Predictors of COVID-19 Vaccine Hesitancy in Virginia (Asal Pilehvari; Jason Ton; Mukundan Ram Mohan; Achla Marathe and Anil Vullikanti) -- Chapter 9 - The Spreading-Activation Framework Does Not Explain the Effects of Degree and Clustering on Spoken Word Recognition (Leo Niehorster-Cook) -- Chapter 10 - Engineering Decentralized Enterprises: Emergent Mission Accomplishment without Centralized Command and Control (Michael Norman; Paul Silvey; Matthew Koehler and Kirbi Joe) -- Chapter 11 - An Agent-Based Approach to Classical Competitive Prices (Jonathan Cogliano, Roberto Veneziani and Naoki Yoshihara) -- Chapter 12 - Machine Learning Reveals Adaptive COVID-19 Narratives in Online Anti-Vaccination Network (Richard Sear; Rhys Leahy; Nicholas Johnson Restrepo; Yonatan Lupu and Neil Johnson) -- Chapter 13 - Agentization of Two Population-Driven Models of Mathematical Biology(John Stevenson).

Additional Edition: Print version: Yang, zining Proceedings of the 2021 Conference of the Computational Social Science Society of the Americas Cham : Springer International Publishing AG,c2022 ISBN 9783030961879

Language: English

DOI: 10.1007/978-3-030-96188-6

UID:

Format: 1 online resource (403 pages)

ISBN: 3-030-77517-8

Series Statement: Springer Proceedings in Complexity

Note: Intro -- Contents -- Editors and Contributors -- Social Impression of Faces: From Prediction to Modification -- 1 Introduction -- 2 Predicting Social Attributes of Faces -- 3 Creating a Large-Scale Facial Impression Dataset -- 4 Validating the Algorithm-Augmented Dataset -- 5 ModifAE: A Modification Model of Social Impressions -- 5.1 Architecture -- 5.2 ModifAE Training Procedure -- 5.3 How ModifAE Works -- 5.4 Qualitative Evaluation -- 5.5 Quantitative Evaluation -- 5.6 Qualitative Interpretations -- 6 Discussion -- References -- Corruption and the Effects of Influence Within Social Networks: An Agent-Based Model of the ``Lava Jato'' Scandal -- 1 Introduction -- 2 Background -- 3 The Model -- 3.1 Generation of Networks -- 3.2 Agents -- 3.3 Initialization of the Model and Agent Interactions -- 4 Results -- 5 Conclusion -- References -- Resistance of Communities Against Disinformation -- 1 Introduction -- 2 Opinion Dynamics -- 3 Model of Conspirators -- 4 Results -- 5 Discussion -- References -- Assessing the Potential of Crowd-Shipping for Food Rescue Logistics Using Agent-Based Modeling -- 1 Introduction -- 2 Models of Crowd-Shipping Systems -- 3 Agent-Based Model -- 3.1 Model Overview -- 3.2 Sub-Model 1: Restaurant Agent Decision-Making -- 3.3 Sub-Model 2: Shelter Assignment -- 3.4 Sub-Model 3: Crowd-Shipper Agent Decision-Making -- 3.5 Initialization -- 4 Experimentation and Results -- 5 Conclusion -- References -- Exogenous Shocks Lead to Increased Responsiveness and Shifts in Sentimental Resilience in Online Discussions -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Data -- 3.2 Conversation Dynamics -- 3.3 Sentiment Transfer -- 3.4 Transfer Entropy -- 4 Results -- 4.1 Conversation Dynamics -- 4.2 Sentiment Transfer -- 4.3 Total Transfer Entropy -- 5 Conclusion -- References -- The Cat and Mouse of Getting Around the Law. , 1 Introduction -- 2 Results -- 3 Optimizing Strategies -- 3.1 Fast and Strong ("All in") -- 3.2 Slow and Strong ("Slow and Aggressive") -- 3.3 Fast and Weak -- 3.4 Slow and Weak ("Do Nothing") -- 4 Discussion -- 5 Conclusion -- References -- The Degree-Dependent Threshold Model: Towards a Better Understanding of Opinion Dynamics on Online Social Networks -- 1 Introduction -- 2 Methods -- 2.1 Data Set and Twitter Analysis Results -- 2.2 Generating Networks -- 2.3 Assigning Thresholds -- 2.4 Running Simulations -- 3 Simulation Results -- 4 Conclusion -- References -- Modeling Genocide: An Agent-Based Model of Bystander Motivations and Societal Restraints -- 1 Introduction -- 1.1 Review of Prior Work -- 1.2 Addressing the Research Gap -- 2 Research Approach -- 2.1 Social Science Theories -- 2.2 ABM Implementation -- 3 Results -- 3.1 Experiment 1: Effect of Contagion and Fear on Violence -- 3.2 Experiment 2: Sensitivity Analysis-System-Level Factors of Restraint () -- 4 Conclusions and Future Work -- References -- Global News Sentiment Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology and Experimentation -- 4 Results -- 4.1 Initial Observation -- 4.2 Comparison of Four Sentiment Analysis Tools -- 4.3 Three Article Processing Approaches -- 5 Discussion -- 6 Conclusion -- References -- An Agent-Based Model of Social Fabric Seen as an Emergent Behavior -- 1 Introduction -- 2 Social Fabric -- 3 Modeling Social Fabric in Cities -- 3.1 Conceptual Model -- 3.2 Agent-Based Model -- 4 Case Study: The Miramar Region -- 4.1 Mobility Patterns and Its Relationship with Perception -- 4.2 Encounters -- 5 Conclusion -- References -- Deep Agent: Studying the Dynamics of Information Spread and Evolution in Social Networks -- 1 Introduction -- 2 Challenge Problem Description -- 3 Methodology -- 3.1 Deep Agent Framework: Architecture and Analysis. , 3.2 Agent-Based Models -- 4 Dataset Description -- 4.1 Evaluation Events and Metrics -- 5 Experimental Results -- 6 Conclusion and Future Work -- References -- Electoral College: Emergent Battlegrounds An Agent-Based Model of Campaign Behavior Change with District Allocation of Electors -- 1 Introduction -- 2 Background -- 3 Methodology -- 4 The Model -- 5 Validation -- 6 Results -- 7 Discussion and Conclusions -- References -- Social Viscosity, Fluidity, and Turbulence in Collective Perceptions of Color: An Agent-Based Model of Color Scale Convergence -- 1 Introduction: Social Viscosity, Fluids, and Turbulence -- 2 Social Meaning and the Analysis of Proximity -- 2.1 Meaning and Viscosity in Color Agents -- 3 An Agent-Based Model of Color Proximity -- 4 Case Study: Nucleation in Circular Color Scales -- 4.1 Methods -- 4.2 All-to-all Interactions -- 4.3 N Nearest-Neighbor Interactions -- 5 Discussion -- 6 Conclusions and Further Work -- References -- Inside the Mind of the Nonfiler: An Agent-Based Modeling Approach -- 1 Introduction -- 1.1 Brief Overview of Nonfilers and IRS Enforcement/Outreach -- 1.2 Current IRS Nonfiler Research -- 1.3 Past Uses of Agent-Based Models (ABMs) at RAAS -- 2 Methods -- 2.1 Agent-Based Model Overview -- 2.2 Econometric Modeling -- 3 Data -- 4 Results -- 4.1 Agent-Based Model -- 5 Discussion -- 5.1 Agent-Based Model -- 6 Conclusions and Future Work -- 6.1 Future Work -- Appendix-Overview, Design Concepts and Details, and Decision Making (ODD + D) Protocol Documentation of the Nonfiler Decision Model -- Purpose -- Entities, State Variables, Scales -- Process Overview and Scheduling -- Design Concepts -- Initialization -- Input Data -- Submodels -- References -- Capturing the Effects of Gentrification on Property Values: An Agent-Based Modeling Approach -- 1 Introduction -- 2 Related Work -- 3 Model Design -- 3.1 Data. , 3.2 Environment -- 3.3 Agent Classes -- 3.4 Gentrification Calculation -- 3.5 Verification -- 4 Results -- 4.1 Gentrification by Supply -- 4.2 Gentrification by Demand -- 5 Discussion and Further Works -- 5.1 Main Results -- 6 Conclusion -- References -- Negative Influence Gradients Lead to Lowered Information Processing Capacity on Social Networks -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- A Complex-Systems Agenda for Influencing Policy Studies -- 1 Introduction -- 1.1 Purpose -- 1.2 Our Definitions -- 1.3 Additional Discussion of Definitions -- 2 Worldview -- 2.1 System Thinking -- 2.2 Confronting Complexity and Wicked Problems -- 2.3 Decision-Making as a Continuing and Messy Process -- 2.4 The Values and Objectives that Drive Decisions -- 2.5 Knowledge, Uncertainty, and Disagreement -- 2.6 Moderation in the Search for Control -- 3 Basis for Reasoning and Inference -- 3.1 Theory, Data, Association, and Causation -- 3.2 Types of Theory -- 4 Analytic Style -- 4.1 Analysis and Reductionism, Both Good and Bad -- 4.2 Character of Analysis: Quantitative Versus Qualitative, and Matters of Rigor -- 4.3 Confronting Uncertainty and Disagreement -- 4.4 Comparing Options -- 4.5 Changing the Questions Asked of Simulation -- 5 Character of Models and Model-Based Analysis -- 5.1 Different Classes of Model -- 5.2 Purpose of Models and Related Issues of Validity -- 5.3 Measures of Outcome -- 5.4 Predict and Act Versus Anticipate Possibilities and Act Adaptively -- 6 Conclusions -- 6.1 Implications for Teaching Policy Studies -- 6.2 Implications for Computational Social Science -- References -- Wealth Dynamics in the Presence of Network Structure and Primitive Cooperation -- 1 Introduction -- 2 Model -- 2.1 Mathematical Formulation -- 2.2 Implementation -- 3 Verification. , 3.1 Agent and Proto Life History -- 3.2 Gini Coefficient History -- 4 Analysis -- 4.1 Gini Coefficient -- 4.2 Life Expectancy -- 4.3 Interpretations, Conjectures, and Next Steps -- 5 Conclusion and Future Work -- References -- Social Primitives: Exploring Spark of Life Collective Behavior in Agent-Based Models -- 1 Introduction -- 2 Examples of Agent-Based Social Primitives -- 2.1 Ring World -- 2.2 Conway-Game of Life -- 2.3 Complexity Adaptive Systems-Page and Miller -- 2.4 Hammond-Tobacco and Policy-Low-Dimensional and High-Dimensional Models -- 3 Taxonomy of Social Primitives -- 3.1 Agent Description -- 3.2 Coding Agents and the Challenge of Implicit Assumptions -- 3.3 Environment Description -- 3.4 Coding the Environment and the Challenge of Implicit Assumptions -- 4 Coding a Social Primitives Model: The SPECscape Model -- 4.1 Agent to Agent Interaction -- 4.2 Agent-Environment Interaction -- 4.3 Anthropomorphic Crossover -- 5 Running the SPECscape Model -- 5.1 SPECscape Model and Gini Index -- 5.2 Four Landscape Starting Points -- 5.3 The Effect of Exogenous Shocks at Various Stages of Model Evolution -- 5.4 Models with and without Proto-institutions -- 6 Conclusion -- 6.1 Elements of Collective Function -- 6.2 Determining Anthropomorphic Leaps -- 6.3 Determining a Parameter-Based Measure of Model Complexity -- 6.4 Possibilities for Increasing the Complexity of SPECscape Model -- Appendix -- References -- Capturing the Production of Innovative Ideas: An Online Social Network Experiment and ``Idea Geography'' Visualization -- 1 Introduction -- 2 Online Social Network Experiment -- 2.1 Experimental Procedure -- 2.2 Collective Design Tasks -- 3 Data Analysis Methods -- 3.1 Doc2Vec -- 3.2 Principal Component Analysis -- 3.3 Idea Geography -- 4 Results -- 4.1 Experiment Session I: Catch Phrase Design -- 4.2 Experiment Session II: Story Design. , 5 Discussions.

Additional Edition: ISBN 3-030-77516-X

Language: English